Introduction

This script builds the map of participation by census area similar to the one created by Kiko Llaneras and Nacho Carretero in this article https://elpais.com/politica/2019/03/28/actualidad/1553783809_455746.html

We will use R and specially the leaflet package

Data

To build the map we need:

Participation data

Participation data that we can download from Ministerio del Interior. Go to the bottom of the page (“Extracción de Datos”) and choose “Congreso” and “Junio 2016”. The webpage will reload and different links will appear. Click on “Mesa”.

The downloaded folder 02201606_MESA contains different files with data about participation and results for the different parties (have a look at the description in the FICHEROS.doc file. The one we will use is 09021606.DAT which contains the data of participation by poll station.

It has fixed width for each field:

participacion <- read.fwf("./data/02201606_MESA/09021606.DAT",  
                          widths=c(2,4,2,1, 
                                   2,2,3,2,4,1, 
                                   7,7,7,7,7,7,7,7,7,7,7,   
                                   1),  
                          colClasses=c(rep("numeric",4),    
                                       rep("character",6),  
                                       rep("numeric",11),   
                                       "character"))

and name the colums (see again FICHEROS.doc for their description)

colnames(participacion) <- c("tipo","year","month","vuelta",    
                          "ccaa","provincia","municipio","distrito","seccion","mesa",   
                          "censo","censo_escrutinio","censo_cere","total_cere", 
                          "votantes_primer","votantes_segundo", 
                          "blanco","nulos","votos","afirmativos","negativos",   
                          "datos_oficiales")

Here is how it looks

head(participacion)
##   tipo year month vuelta ccaa provincia municipio distrito seccion mesa
## 1    2 2016     6      1   01        04       003       02    002     B
## 2    2 2016     6      1   01        04       009       01    001     U
## 3    2 2016     6      1   01        04       013       04    001     U
## 4    2 2016     6      1   01        04       013       04    004     U
## 5    2 2016     6      1   01        04       013       07    002     U
## 6    2 2016     6      1   01        04       013       07    007     A
##   censo censo_escrutinio censo_cere total_cere votantes_primer
## 1   516              516          0          0             166
## 2   162              162          0          0              63
## 3   706              706          0          0             326
## 4   702              702          0          0             272
## 5   774              774          0          0             315
## 6   632              632          0          0             269
##   votantes_segundo blanco nulos votos afirmativos negativos
## 1              220      2     1   310           0         0
## 2               80      2     1   120           0         0
## 3              421      3     0   571           0         0
## 4              348      5     1   490           0         0
## 5              402      2     5   526           0         0
## 6              346      4     2   496           0         0
##   datos_oficiales
## 1               S
## 2               S
## 3               S
## 4               S
## 5               S
## 6               S

We are going to analyze the participation by census area (sección censal). To do that we have to aggregate the poll stations (mesas) that belong to the same census area. We introduce a new field which is a unique number for each census area

participacion$CUSEC <- paste0(participacion$provincia,
                              participacion$municipio,
                              participacion$distrito,
                              participacion$seccion)    
participacion$CUSEC <- str_trim(participacion$CUSEC)

and finally aggregate by census area and aalculate participation percentage in each of them.

df.participacion <- participacion %>%   
  group_by(provincia,municipio,distrito,seccion,CUSEC) %>%  
  summarize(total_votos=sum(votos),total_censo=sum(censo)) %>%  
  mutate(participacion = total_votos/total_censo*100)

Census areas boundaries

In the map we are going to show each census area and its participation. We need the boundaries (polygons) for each of them. We can download the polygons in the shapefile (SHP) format from from the INE http://www.ine.es/censos2011_datos/cen11_datos_resultados_seccen.htm

Let’s import them

require(rgdal)  
secciones <- readOGR(dsn="./data/cartografia_censo2011_nacional/",layer="SECC_CPV_E_20111101_01_R_INE",verbose = F)

And change their geographical projection for its use later

WGS84 <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs")    
secciones <- spTransform(secciones,CRSobj=WGS84)

Merge data

Finally we are going to merge the participation data with the geographical areas. Note that each census area in the secciones object is given a unique CUSEC id which is the same we used for the participation data. So we merge both datasets using it.

secciones <- merge(secciones,df.participacion,by="CUSEC")

Visualize the data

To visualize it we are going to use the leaflet library and Carto Positron tiles. Let’s do it only for the Madrid province (code “28”)

smad <- secciones[secciones$CPRO=="28",]    
pal <- colorBin(palette = "BrBG", domain = smad$participacion, bins = 10)   
smad %>% leaflet() %>% addProviderTiles(providers$CartoDB.Positron) %>% 
  addPolygons(fillColor = ~ pal(participacion),fillOpacity = 0.5,color = "white",weight = 1,    
              label = ~ paste0(round(participacion,2),"%")) %>%     
  addLegend("bottomright", pal = pal, values = ~participacion)

Or the provinces in Catalonia

cod_cataluna <- c("08","17","25","43")
scat <- secciones[secciones$CPRO %in% cod_cataluna,]
pal <- colorBin(palette = "BrBG", domain = scat$participacion, bins = 10)   
scat %>% leaflet() %>% addProviderTiles(providers$CartoDB.Positron) %>% 
  addPolygons(fillColor = ~ pal(participacion),fillOpacity = 0.5,color = "white",weight = 1,    
              label = ~ paste0(round(participacion,2),"%")) %>%     
  addLegend("bottomright", pal = pal, values = ~participacion)
## Warning in RColorBrewer::brewer.pal(max(3, n), palette): n too large, allowed maximum for palette BrBG is 11
## Returning the palette you asked for with that many colors

## Warning in RColorBrewer::brewer.pal(max(3, n), palette): n too large, allowed maximum for palette BrBG is 11
## Returning the palette you asked for with that many colors